Inference Observability
High-resolution, inference-native observability across models, engines, and GPUs, with built-in AI debugging.
NVIDIA
PyTorch
Hugging Face
vLLM
PyTorchHugging FacevLLMInference profiling
Continuous, high-resolution profiling timelines exposing operation durations and resource utilization across inference workloads.
LLM tracing
LLM generation tracing with per-step timing, token throughput, and latency breakdowns for major inference frameworks.
System metrics
System-level metrics for inference engines and hardware (CPU, GPU, accelerators).
Error monitoring
Error monitoring for device-level failures, runtime exceptions, and inference errors.
AI debugging
AI debugging to explain performance data and errors, identify bottlenecks, and recommend optimizations across the inference stack.